This is a Python class SudokuSolverAnnealing that uses the Simulated Annealing algorithm to solve Sudoku puzzles. The SudokuSolverAnnealing class takes a 9x9 list representing a Sudoku board and returns a solution to the puzzle. The algorithm also accepts optional parameters to control its behavior, including the maximum number of iterations, initial temperature, and cooling rate.
This project requires Python 3.6 or higher. To use the SudokuSolverAnnealing class, simply copy the code into your project or import it as a module.
The SudokuSolverAnnealing class is used to solve Sudoku puzzles using the Simulated Annealing algorithm. To use it, first create an instance of the class with a 9x9 list representing a Sudoku board, and optionally set any desired parameters. Then, call the solve method on the instance to obtain a solution to the puzzle.
from SudokuSolverAnnealing import SudokuSolverAnnealing
# Define a Sudoku board as a 9x9 list.
board = [[0,0,0,0,8,0,9,6,2],
[0,0,8,5,1,0,0,0,0],
[0,6,0,0,9,0,1,0,0],
[0,8,4,1,6,9,7,0,3],
[3,0,0,7,0,0,2,1,0],
[0,0,7,0,2,0,4,0,0],
[0,0,1,2,7,5,6,4,0],
[0,7,2,9,0,0,0,0,1],
[5,4,0,6,0,0,8,0,0]]
# Create an instance of the SudokuSolverAnnealing class and solve the puzzle.
solver = SudokuSolverAnnealing(board)
solution = solver.solve_sudoku()
# Print the solution.
solver.print_sudoku(solution)
The code above defines a Sudoku board as a 9x9 list and passes it to an instance of the SudokuSolverAnnealing class. The solve_sudoku method is then called on the instance to obtain a solution to the puzzle. Finally, the print_sudoku method is used to print the solution to the console.
The SudokuSolverAnnealing class accepts the following parameters:
board(list): A 9x9 list representing the Sudoku board. The board should contain integers or 0 to represent empty cells.max_iteration(int): The maximum number of iterations the algorithm will perform before stopping. Default is 100000.initial_temperature(float): The initial temperature for the simulated annealing algorithm. Default is 0.6.cooling_rate(float): The rate at which the temperature decreases during the simulated annealing algorithm. Default is 0.999.
If you want to contribute to this project, there are several ways you can do so:
- Submit bugs and feature requests: If you find a bug or have a feature request, please submit an issue on the GitHub repository.
- Submit pull requests: If you have a fix or improvement for the code, feel free to submit a pull request on the GitHub repository. Please make sure your code is well-documented and tested.
- Spread the word: If you like this project, please share it with your friends and colleagues.